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| Content Provider | ACM Digital Library |
|---|---|
| Author | Dickerson, Robert F. Gorlin, Eugenia I. Stankovic, John A. |
| Abstract | Depression is a major health issue affecting over 21 million American adults that often goes untreated, and even when undergoing treatment it is hard to monitor the effectiveness of the treatment. To address these issues, we have created a real-time depression monitoring system for the home. This system runs 24/7 and can potentially detect the early signs of a depression episode, as well track progress managing a depressive illness. A cohesive set of integrated wireless sensors, a touch screen station, mobile device, and associated software deliver the above capabilities. The data collected are multi-modal, spanning a number of different behavioral domains including sleep, weight, activities of daily living, and speech prosody. The reports generated by this aggregated data across multiple behavioral domains are aimed to provide caregivers with more accurate and thorough information about the client's current functioning, thus helping in their diagnostic assessment and therapeutic treatment planning as well for patients in the management and tracking of their symptoms. We present data of a case study showing the value of the system, deployed over a period of two weeks in a home during a depressive episode. Larger scale studies are planned for the future. |
| Starting Page | 1 |
| Ending Page | 10 |
| Page Count | 10 |
| File Format | |
| ISBN | 9781450309820 |
| DOI | 10.1145/2077546.2077552 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2011-10-10 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Clinical depression Emotional health monitoring |
| Content Type | Text |
| Resource Type | Article |
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